Identify the top areas for improvement across your existing ML projects and pinpoint any high priority projects that will be needed to meet your overall goals in pathology.
In 1-2 weeks, you’ll know where to prioritize your ML efforts.
Machine learning research progresses rapidly but which advancements are worth implementing for your application?
Machine learning projects are complex and iterative with uncertain outcomes. It’s not simply software but the intersection of software, engineering, and science. And this field moves fast. Deep learning barely existed a decade ago, and the tools and research are constantly evolving. Unsuccessful or unneeded projects can waste a lot of time and money. Prioritizing your ML projects requires understanding the challenging aspects of each and recognizing new opportunities.
You’ve tried to hire the best talent, but ML experts are hard to find – and expertise in your domain is even more elusive. How will you know if the path you’re on aligns with your overall goals? Is there an existing tool to accomplish something you’re implementing from scratch? Or recent research demonstrating a novel application that could create a real impact for your customers?
Clear machine learning strategy for your team
Imagine having a clear set of priorities for your team. You’ll know which projects to prioritize to meet your goals. Before you start any new ML projects, you’ll know what phase the existing ones are in, which should be prioritized, and learn about any new projects that are needed to reach your goals.
Your team wouldn't get stuck debating which projects to pursue or going down rabbit holes evaluating each. You'll have a recognized expert in ML only a phone call away.
The impact on your business of a successful ML product or service is immense. Set your team on the path to success.
Get a customized Machine Learning Assessment evaluating how well your projects align with your goals
Using our proprietary process, we'll assess your ongoing and planned projects in combination with your overall goals. We’ll outline our findings in a report that will provide a strategic plan for advancing your ML capabilities and ensuring that they can support your goals.
- Clear priorities for your ML team
- Decreased uncertainty on where to focus ML efforts
- Save time by incorporating the latest and greatest tools and techniques
- Learn about recent research advancements that can create novel solutions for your customers
- Increased likelihood of success
Here’s how it works:
We will have two meetings over Zoom during a 1-2 week period. You’ll start by filling out a questionnaire with some background information about your goals and existing and planned projects. We’ll dive deeper into each in our first meeting, examining the desired outcomes for your team and the state and challenges of each ongoing project. We might have some questions for you to follow up on afterwards.
In our second meeting, we’ll present our findings. We’ll explain the priorities we’ve assigned to different projects and discuss any new opportunities that we’ve identified for you to consider.
You will receive a report reviewing each of your existing and potential new projects. The report will conclude by ranking each project with respect to the current phase of development, importance for meeting your goals, data availability, and level of difficulty for implementation.
100% money-back guarantee!
If you don’t feel the ML Assessment is the right fit for you, just let us know at the end of our kickoff meeting and we’ll refund your payment in full.
Don’t just take our word for it…
Pixel Scientia provides valuable insights for Gestalt's image analysis product development. Heather has deep understanding of digital pathology and machine learning and their application to whole slide images. Her in-depth review of the current state of the art research has enabled Gestalt to rapidly focus our machine learning efforts on approaches that are yielding value for our pathologists and their patients.
Heather's knowledge of the current state of the art within the digital pathology field is second to none. Consultation on best practice approaches for 'deep learning model classification performance' and insight into digital research perspectives were very beneficial. Discussions of prior art enabled our team to focus on novel research and refine our current AI methodologies for clinical research.
Still have questions?
What happens after I apply?
We’ll schedule a short call to confirm that this package is suitable for your project. Then we’ll send over a short contract. Once you submit your payment, you’ll receive an email with a link to a questionnaire. At the end of the questionnaire you’ll be able to schedule our kickoff call.
Will you sign an NDA before we start?
The contract for this ML Assessment will include confidentiality and non-disclosure provisions.
We already have a great ML team. Why do we need you?
Maybe you don't need me. If your team is spending most of their time keeping up with the state-of-the-art and can outline a clear roadmap, you might not.But if your team is spending most of their time training algorithms, that's where we come in. It is our job to stay at the forefront of the field, specifically at the intersection of machine learning, computer vision, and pathology. Through literature reviews and observations across multiple projects, we develop best practices for applying ML to pathology images and tactics for adapting new advances.
You and your team know your data and specific application better than we ever will. In developing the ML Assessment, we build upon your team’s expertise and combine it with our knowledge of the field to get you on the path to a successful ML solution.
What’s next after the assessment? Can you help us with a specific project?
After completing this assessment, we have a couple of options. We could start by diving deeper into a particular high priority project. Our ML Roadmap offer is uniquely positioned to develop a clear plan for an ML project using best practices for pathology. Alternatively, our ML Advisor monthly service can support your team across multiple projects. We’ll keep you abreast of the latest research for your application, provide feedback on algorithm development, hiring advice, and more.
Still not sure if this is the right package for you?
Schedule a Strategy Session, and we’ll help you determine if this is a good fit.
Who are you, anyway?
Pixel Scientia Labs is led by Heather Couture. I have 16 years of experience in machine learning, 10 of those with applications to pathology. While I have no medical training, I do have a PhD in Computer Science and have published in top-tier computer vision and medical imaging venues. I write regularly on LinkedIn, for my newsletter Pathology ML Insights, and for a variety of trade publications. You may have heard me on podcasts or at conferences.
My team and I help our clients accelerate their machine learning projects with best practices for pathology images. We make use of the latest ML research to amplify their results and support their in-house team for the long term. Our mission is to fight cancer with AI – and we do that by strengthening the ML component of our clients’ most impactful projects.
Availability is limited
We only take on two new clients a month with this ML Assessment offer. Scheduling is first come, first served. The sooner you apply, the sooner you will get a clear set of priorities for your ML team.